Realization of Dynamically Adaptive Weather Analysis and Forecasting in LEAD: Four Years Down the Road

Authors:
Lavanya Ramakrishnan;Yogesh Simmhan;Beth Plale
Affiliations:
School of Informatics, Indiana University, Bloomington, IN 47045,;School of Informatics, Indiana University, Bloomington, IN 47045,;School of Informatics, Indiana University, Bloomington, IN 47045,
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007
Year:
2007

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Abstract

Linked Environments for Atmospheric Discovery (LEAD) is a large-scale cyberinfrastructure effort in support of mesoscale meteorology. One of the primary goals of the infrastructure is support for real-time dynamic, adaptive response to severe weather. In this paper we revisit the conception of dynamic adaptivity as appeared in our 2005 DDDAS workshop paper, and discuss changes since the original conceptualization, and lessons learned in working with a complex service oriented architecture in support of data driven science.